
Higher Education - IoT Vulnerability and Risk Management
Challenge
As cyberattacks on higher education increase, technology teams struggle to sift through the noise and quickly find and mitigate IoT device vulnerabilities and risks.
High vulnerability rates
of IoT devices on higher education campuses are vulnerable to medium or high-severity attacks
Lack of security measures
of educational institutions report insufficient security measures for their IoT devices
Frequent attacks
of higher education institutions have experienced at least one IoT-related security incident in the past year
Solution
With Cylera, technology teams in higher education can achieve real-time visibility into vulnerabilities and comprehensive risk insight for all IoT devices in their inventory
Proactively identify, prioritize, and mitigate IoT device vulnerabilities and risks to ensure safe, reliable campus operations




Accurate Vulnerability Detection
Cylera leverages advanced machine learning algorithms and real-time monitoring for fast, accurate IoT device vulnerability detection. This allows technology leaders in higher education to quickly identify vulnerable IoT devices.
Real-World Risk Intelligence
Cylera uses machine learning and artificial intelligence to correlate IoT device vulnerabilities from multiple third-party sources (including the NIST NVD and IoT device manufacturer vulnerability databases). Cylera then combines this data with network behaviors and indicators of compromise to pinpoint IoT device risks in real time.








Risk Scoring with Prioritization
Cylera delivers highly accurate risk scoring and prioritization for IoT devices used in higher education, based on vulnerability assessment results, device type, device behavioral analysis, device dependencies, usage telemetry, indicators of compromise (IOCs), and secondary controls. This helps focus mitigation efforts by reducing alert noise and shortening remediation lists.
Guided Remediation
Cylera provides precise, step-by-step remediation guidance tailored to each identified vulnerability and risk. This enables campus IT security teams to address IoT device risks quickly and with confidence. It also reduces errors and uncertainty and ensures all team members follow the same uniform security best practices.




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